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Interactively Exploring Supply and Demand in the UK Independent Music Scene

  • Matt McVicarEmail author
  • Cédric Mesnage
  • Jefrey Lijffijt
  • Tijl De Bie
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)

Abstract

We present an exploratory data mining tool useful for finding patterns in the geographic distribution of independent UK-based music artists. Our system is interactive, highly intuitive, and entirely browser-based, meaning it can be used without any additional software installations from any device. The target audiences are artists, other music professionals, and the general public. Potential uses of our software include highlighting discrepancies in supply and demand of specific music genres in different parts of the country, and identifying at a glance which areas have the highest densities of independent music artists.

Keywords

Music Genre Music Professional Music Artist Tower Hamlet Independent Poisson Random Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Bellogín, A., de Vries, A.P., He, J.: Artist popularity: do web and social music services agree? In: Proc. of ICWSM, pp. 673–676 (2013)Google Scholar
  2. 2.
    Hauger, D., Schedl, M., Košir, A., Tkalčič, M.: The million musical tweets dataset: what can we learn from microblogs. In: Proc. of ISMIR, pp. 189–194 (2013)Google Scholar
  3. 3.
    Price, R., Bonett, D.: Estimating the ratio of two poisson rates. Computational Statistics & Data Analysis 34(3), 345–356 (2000)zbMATHMathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Matt McVicar
    • 1
    Email author
  • Cédric Mesnage
    • 1
  • Jefrey Lijffijt
    • 1
  • Tijl De Bie
    • 1
  1. 1.Intelligent Systems LabUniversity of BristolBristolUK

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